Using percentage accuracy to measure neural network predictions in Stock Market movements

Neurocomputing

Volumn 10, Issue 3, 1996, Pages 237-250

  Brownstone, D ^a  

^a NONE   (United Kingdom)

Author keywords

Accuracy; Market; Neural network; Percentage; Prediction; Stock

Indexed keywords

FINANCIAL DATA PROCESSING; FORECASTING; INDUSTRIAL ECONOMICS; MARKETING; REGRESSION ANALYSIS;

MEAN SQUARE ERROR; MULTIPLE LINEAR REGRESSION; PERCENTAGE ACCURACY; ROOT MEAN SQUARE ERROR; STOCK MARKET MOVEMENTS;

NEURAL NETWORKS;

ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; PRIORITY JOURNAL;

EID: 0030130831     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/0925-2312(95)00052-6     Document Type: Article

References (5)

1. B. Freisleben, Stock market prediction with back propagation networks, in F. Belli and F.J. Radermacher (Eds.), Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Proc. 5th Int. Conf. IEA / AIE-92 (Paderborn, Germany, June 1992, Springer-Verlag).
2. G-S. Jang et al., Intelligent stock trading system with price trend prediction and reversal recognition using dual-module neural networks, J. Applied Intelligence 3 (1993) 225-248.
3. N. Baba and M. Kozaki, An intelligent forecasting system of stock price using neural networks, IEEE / INNS Int. Joint Conf. on Neural Networks, Vol. I, Baltimore, Maryland, USA (June 7-11, 1992) (New York, USA, Institute of Electrical and Electronic Engineers).
4. T. Masters, Practical Neural Network Recipes in C + +. (Academic Press, 1993).
5. NeuroShell User Guide (1988-1991), Ward Systems Group Inc., Maryland, USA.